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We're here to help you find itThe "Data Wrangling and Visualization for Data Analyst" course is a comprehensive program designed to equip learners with the necessary skills to manipulate and present data effectively. Throughout the course, students will understand the data science workflow, grasp data wrangling and visualization concepts, and become proficient in using tools like R, Python, SQL, Power BI, Tableau, and Java. Learners will start by acquiring and extracting data from various sources, including databases and the web, and then move on to cleaning and preprocessing to ensure data quality. The course emphasizes the importance of exploratory data analysis (EDA) to uncover patterns and insights. Advanced modules will introduce interactive visualizations and specialized techniques like geospatial data visualization. Finally, the course culminates with lessons on how to effectively present insights through storytelling with data and create compelling data presentations and reports. This course will be valuable for those seeking to hone their data analysis skills and effectively communicate their findings.
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Classroom Training price is on request
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♱ Excluding VAT/GST
Classroom Training price is on request
You can request classroom training in any city on any date by Requesting More Information
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4-Hour Sessions
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To ensure a successful learning experience in the Data Wrangling and Visualization for Data Analyst course, participants are expected to have the following minimum prerequisites:
Please note that while prior experience with specific data analysis tools (e.g., Power BI, Tableau) is helpful, it is not mandatory for enrollment in this course. The training is designed to introduce these tools and guide students through practical applications.
The course 'Data Wrangling and Visualization for Data Analysts' equips learners with key skills in data processing and graphical representation.
Target audience and job roles for the course include:
Introduction to Learning Outcomes: Gain proficiency in data wrangling and visualization techniques, utilizing tools such as R, Python, SQL, Power BI, and Tableau to extract, clean, transform, and communicate data insights effectively.
Learning Objectives and Outcomes:
